Search Results for author: S. Mohammadzadeh

Found 4 papers, 1 papers with code

Efficient Covariance Matrix Reconstruction with Iterative Spatial Spectrum Sampling

no code implementations2 Sep 2023 S. Mohammadzadeh, V. H. Nascimento, R. C. de Lamare, O. Kukrer

This work presents a cost-effective technique for designing robust adaptive beamforming algorithms based on efficient covariance matrix reconstruction with iterative spatial power spectrum (CMR-ISPS).

Study of Robust Adaptive Beamforming with Covariance Matrix Reconstruction Based on Power Spectral Estimation and Uncertainty Region

no code implementations18 Mar 2023 S. Mohammadzadeh, V. H. Nascimento, R. C. de Lamare, O. Kukrer

In this work, a simple and effective robust adaptive beamforming technique is proposed for uniform linear arrays, which is based on the power spectral estimation and uncertainty region (PSEUR) of the interference plus noise (IPN) components.

Predicting Mechanically Driven Full-Field Quantities of Interest with Deep Learning-Based Metamodels

1 code implementation24 Jul 2021 S. Mohammadzadeh, E. Lejeune

However, full-fidelity simulation techniques such as Finite Element Analysis can be prohibitively computationally expensive when they are used to explore the massive input parameter space of heterogeneous materials.

Low-Cost Maximum Entropy Covariance Matrix Reconstruction Algorithm for Robust Adaptive Beamforming

no code implementations28 Dec 2020 S. Mohammadzadeh, V. H. Nascimento, R. C. de Lamare

In this letter, we present a novel low-complexity adaptive beamforming technique using a stochastic gradient algorithm to avoid matrix inversions.

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